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Artificial intelligence-powered whole-slide image analyzer reveals a distinctive distribution of tumor-infiltrating lymphocytes in neuroendocrine tumors and carcinomas

Hyung-Gyo Cho et al. — ASCO(2022)



Immune checkpoint inhibitors (ICIs) have shown promising treatment outcomes for various types of tumors. However, in neuroendocrine tumors and carcinomas (NET/NEC), ICI has proven to be applicable for only limited cases. In addition, little is known about the immunoprofile of NET/NEC. Here we investigate the landscape of tumor-infiltrating lymphocytes (TIL) using artificial intelligence (AI)-powered H&E whole-slide image (WSI) analyzer to elucidate the tumor microenvironment of NET/NEC.


A total of 240 H&E stained pathologic slides diagnosed with NET/NEC were obtained from Ajou University Medical Center in Korea (from January 2020 to December 2021). For spatial TIL analysis, we used Lunit SCOPE IO, an AI-powered H&E WSI analyzer, which identifies and quantifies TIL within the cancer or stroma area. The AI was developed with a 13.5 x 109 μm2 area and 6.2 x 106 TIL from 17,849 H&E WSI of multiple cancer types, annotated by 104 board-certified pathologists. Intra-tumoral TIL, stromal TIL, and combined (cancer + stroma) TIL density were defined as the TIL count divided by the area of interest respectively. NET with histological grade 1 and 2 were labeled as low grade and NET with histological grade 3 and together with NEC were labeled as high grade. Primary origins of the NET/NEC were grouped by colorectum, stomach, small intestine, hepatopancreatobiliary, lung, and other organs (including anus, appendix, breast, cervix, and larynx).


Total slides classified as low grade and high grade were 211 and 29, respectively; 175 samples were from colorectal, 19 from stomach, 16 from small intestine, 16 from hepatopancreaticobiliary, seven from lung, and seven from other organs.

The median intra-tumoral TIL, stromal TIL, and combined TIL density were 4.2/mm2 (IQR 1.718 - 11.478), 139.1/mm2 (IQR 75.4 - 313.9), and 62.4/mm2 (IQR 36.3 - 162.6), respectively. The median intra-tumoral TIL density was significantly higher in patients with high grade NET/NEC compared with low grade (11.9/mm2 [IQR 4.51 - 30.9] vs 3.45/mm2 [IQR 1.63 - 9.81], p < 0.001). However, statistical differences in stromal TIL density and combined TIL density were not observed between low grade and high grade NET/NEC. The highest intra-tumoral TIL density in the group classified according to primary origins was lung (n=7, median: 16.5/mm2, IQR 5.01 - 34.1) and was followed by stomach (n=19, median: 11.8/mm2, IQR 8.64 - 20.8), and small intestine (n=16, median: 7.23/mm2, IQR 4.12 - 25.2).


AI-powered TIL analysis reveals that the intra-tumoral TIL density is significantly higher in high grade NET/NEC than low grade NET. Our findings align with recent evidence that ICIs are effective against large cell NEC and small cell carcinoma. Therefore, AI-powered TIL analysis should be investigated as a predictive biomarker for ICI response in NET/NEC.

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1Hyung-Gyo Cho, 1Wonkyung Jung, 1Soo Ick Cho, 1Ji-won Shin, 1Gahee Park, 1Jimin Moon, 1Minuk Ma, 1Jeongun Ryu, 1Mohammad Mostafavi, 1Seonwook Park, 1Sergio Pereira, 1Kyunghyun Paeng, 1Donggeun Yoo, 1Chan-Young Ock, 2Seokhwi Kim

1Lunit Inc., Seoul, Republic of Korea. 2Ajou University School of Medicine, Suwon, Republic of Korea


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